Volume 3 - Issue 1 - DBU Journal for K-12 Educational Research - Page 34

32 After the procedure was conducted in SPSS, the researcher analyzed results to examine the hypotheses associated with the research question. Significance for the results was set at a p -value, p > .05. According to Yockey (2011), “a p -value indicates the exact probability of obtaining the specific result if the null hypothesis is true” (p. 60). When examining results, if the p < .05, the results would be considered significant, and the researcher would reject the null hypothesis. On the other hand, if p > .05, the results would not be considered significant and the null hypotheses would not be rejected. For RQ1, p = .274, which meant p > .05. In analysis, since p > .05, for RQ1 the null hypothesis was not rejected. This meant when the summer program was added into consideration, participation in the summer program did not have a significant impact on TELPAS Reading scale scores. RQ2 examined TELPAS Reading scale scores for students who participated in the TELPAS Reading exam in both Grades 9 and 10. The question was created to determine if students who participated in a summer accelerated program between Grades 9 and 10 showed higher TELPAS Reading scale scores than those students who did not participate in the summer program. As with RQ1, a stepwise multiple regression analysis was conducted. Two models were created for this analysis, with both models specifying 2017 TELPAS Reading scale scores as the dependent variable. For Model 1, the independent variables were the same as in RQ1, 2016 TELPAS Reading scale scores, 2016 TELPAS Reading rating, and the number of years in U.S. schools. Model 2 contained the same variables as Model 1, but it added program participation as an independent variable. In analyzing results, for Model 1, R 2 = .668, meaning 66.8% of the variance in the dependent variable, 2017 TELPAS Reading scale score, was accounted for by the three independent variables in the model. For Model 2, R 2 = .670, meaning 67.0% of the variance in 2017 TELPAS Reading scale scores was accounted for in the four independent variables in that model, with participation in the summer program being the fourth independent variable in that model. In analyzing this result, ∆R 2 = .002, which was a small change between the two models. For Model 2, with program participation added, p = .172. For RQ 2 , since p > .05 the null hypothesis was not rejected, meaning participation the summer accelerated reading program was not a significant indicator of student scores on the 2017 TELPAS Reading exam. As with both RQ1 and RQ2, a stepwise multiple regression analysis was conducted for RQ3. Two models were created for this analysis, with both models specifying 2017 STAAR EOC English II scale scores as the dependent variable. For Model 1, the independent variables were 2016 TELPAS Reading scale scores, 2016 TELPAS Reading rating, 2017 TELPAS Reading scale scores, 2016 STAAR EOC English I scores, and the number of years in U.S. schools. Model 2 contained the same variables as Model 1, but it added program participation as an independent variable. In reviewing the model summary of findings for RQ3. For Model 1, R 2 = .619, meaning 61.9% of the variance in the dependent variable, 2017 STAAR EOC English II scale score, was accounted for by the five independent variables in the model. For Model 2, R 2 = .619, meaning 61.9% of the variance in 2017 STAAR EOC English II scale scores were accounted for in the six independent variables in that model, with participation in the summer program being the sixth independent variable in that model. In analyzing results, ∆R 2 = .000, which represented no change between the two models. For Model 2, with program participation added, p = .952. For RQ3, since p > .05 the null hypothesis was not rejected, meaning participation in the summer accelerated reading program was not a significant indicator of student scores on the 2017 STAAR EOC English II exam. Table 1 provides a summary of results for RQ1, RQ2, and RQ3. In considering RQ4, the researcher examined the relationship between Texas English Language Proficiency Assessment System Reading rate and participation in the summer program. For RQ4, a chi-square statistical analysis was performed to determine if a significant difference occurred between the observed distribution of TELPAS Reading rating and program participation and the expected distribution should the null hypothesis be true. Should the null hypothesis be true, it would be determined no relationship existed between program participation and TELPAS Reading rating. A chi-square crosstabulation table provided results for the analysis conducted for RQ4. In the table, the Tim E. Baxter, Ed.D.